2 citations · 4 across the 6 of their papers we have counts for
6 papers
Do as I Say, Not as I Do: Instruction-Induction Conflict in LLMs
Carolina Camassa, Derek Shiller
Language models are trained to follow instructions, but they are also powerful pattern completers. What happens when these two objectives conflict? We construct conversations in wh…
Prompting for Policy: Forecasting Macroeconomic Scenarios with Synthetic LLM Personas
Giulia Iadisernia, Carolina Camassa
We evaluate whether persona-based prompting improves Large Language Model (LLM) performance on macroeconomic forecasting tasks. Using 2,368 economics-related personas from the Pers…
Chat Bankman-Fried: an Exploration of LLM Alignment in Finance
Claudia Biancotti, Carolina Camassa, Andrea Coletta +2
Advancements in large language models (LLMs) have renewed concerns about AI alignment - the consistency between human and AI goals and values. As various jurisdictions enact legisl…
Legal Minds, Algorithmic Decisions: How LLMs Apply Constitutional Principles in Complex Scenarios
Camilla Bignotti, Carolina Camassa
In this paper, we conduct an empirical analysis of how large language models (LLMs), specifically GPT-4, interpret constitutional principles in complex decision-making scenarios. W…
Legal NLP Meets MiCAR: Advancing the Analysis of Crypto White Papers
Carolina Camassa
In the rapidly evolving field of crypto assets, white papers are essential documents for investor guidance, and are now subject to unprecedented content requirements under the Euro…
Loquacity and Visible Emotion: ChatGPT as a Policy Advisor
Claudia Biancotti, Carolina Camassa
ChatGPT, a software seeking to simulate human conversational abilities, is attracting increasing attention. It is sometimes portrayed as a groundbreaking productivity aid, includin…